clear all 
version 18 
capture log close 
set more off 

cd "SET YOUR CD" 
use "data all countries.dta", clear

**********Data prep************
drop if ccode==752 //drop swedish observations

*Straightliners from first questions* 
egen sdQ1vars = rowsd(q1_1 q1_2 q1_3 q1_4 q1_5 q1_6 q1_7 q1_8 q1_9 q1_10 q1_11 q1_12 q1_13 q1_14 q1_15 q1_16 q1_17 q1_18 q1_19 q1_20)
ta qcountry sdQ1vars if sdQ1vars==0

drop if sdQ1vars == 0

*Straightliners from objective left/right
egen sdQ9vars = rowsd(q9_1 q9_2 q9_3 q9_4 q9_5 q9_6)

ta qcountry sdQ9vars if sdQ9vars==0
drop if sdQ9vars == 0

**MISC** 
rename qcountry country
label var country Country

label var q10_1 "Trust: Tax authorities"
label var q10_2 "Trust: The public administration"
label var q10_3 "Trust: The police"
label var q10_4 "Trust: The courts"
label var q10_5 "Trust: Political parties"
label var q10_6 "Trust: Government"
label var q10_7 "Trust: Parliament"
label var age_3 "Age: 3 categories"

************DEPENDENT VARIABLES*************
qui tab q1_9
clonevar fuel_rationing=q1_9 

qui tab q1_5 
clonevar food_rationing=q1_5

recode fuel_rationing 1/3=0 4/5=1, gen(fuel_ration_accept)
recode food_rationing 1/3=0 4/5=1, gen(food_ration_accept)

recode fuel_rationing 1/2=1 3=2 4/5=3, gen(fuel_ration_infavor)
recode food_rationing 1/2=1 3=2 4/5=3, gen(food_ration_infavor)


************INDEPENDENT VARIABLES*************** 

*Fairness 
label var Q5d "Perceived fairness [Q5d]" 
label val Q5d fairness 
label def fairness 1"1" 2"2" 3"3" 4"4" 5"5" 
label values Q5d fairness 
clonevar fairness=Q5d 

*Effectivenss 
label var Q5e "Perceived effectiveness [Q5e]"
label val Q5e effectiveness 
label def effectiveness 1"1" 2"2" 3"3" 4"4" 5"5" 
label values Q5e effectiveness 
clonevar effectiveness=Q5e 

*Intrusiveness 
label var Q5f "Perceived intrusiveness [Q5f]" 
label val Q5f intrusiveness 
label def intrusiveness 1"1" 2"2" 3"3" 4"4" 5"5" 
label values Q5f intrusiveness 
clonevar intrusiveness=Q5f 

recode intrusiveness 1=5 2=4 3=3 4=2 5=1, gen(intrusive_rev)
label var intrusive_rev "Intrusiveness" 
label val intrusive_rev Intrusiveness 
label def intrusive_rev 1"1" 2"2" 3"3" 4"4" 5"5" 
label values intrusive_rev intrusive_rev 




*Fairness effectiveness intrusiveness 3-gradig

recode fairness 1/2=1 3=2 4/5=3, gen(fair_3)
label def fair_3 1"Unfair" 2"Neither fair nor unfair" 3"Fair" 
label values fair_3 fair_3

recode effectiveness 1/2=1 3=2 4/5=3, gen(effective_3)
label def effective_3 1"Ineffective" 2"Neither effective nor ineffective" 3"Effective" 
label values effective_3 effective_3 

recode intrusiveness 1/2=1 3=2 4/5=3, gen(intrusive_3)
label def intrusive_3 1"Reduce freedom" 2"Neither increase nor reduce freedom" 3"Increase freedom" 
label values intrusive_3 intrusive_3 


*Left-right reversed
recode q8_1 99=., gen(lr) //left-right self-placement (1052 prefer not to answer). 0 = to the far left, 10 = to the far right. 
label var lr "Ideology: Left-right self-placement [q8_1]"
label val lr q8_1
drop q8_1
gen lr_rev=10-lr //reverse lr. 0 = to the far right, 10 = to the far left 
label define lr_rev 0 "0" 10 "10"
label values lr_rev lr_rev 
label var lr_rev "Ideology: Right-left self-placement [q8_1 reversed]"

*Left-right 3-step* 
recode lr_rev 0=1 1=1 2=1 3=1 4=1 5=2 6=3 7=3 8=3 9=3 10=3, gen(lr_rev_3)
label def lr_rev_3 1 "Right" 2 "Middle" 3 "Left"
label values lr_rev_3 lr_rev_3 

*Objective ideology
corr q9_1 q9_2 q9_3 q9_4 q9_5 q9_6 

gen q9_2_rev=6-q9_2 
gen q9_3_rev=6-q9_3 
gen q9_6_rev=6-q9_6 

gen lr_obj = (q9_1 + q9_2_rev + q9_3_rev + q9_6_rev + q9_4 + q9_5) / 6

gen lr_obj_cat = . 
replace lr_obj_cat = 1 if lr_obj <=2 // Right
replace lr_obj_cat = 2 if lr_obj > 2 & lr_obj <=3 // Center
replace lr_obj_cat = 3 if lr_obj > 3 //Left 
label def lr_obj_cat 1 "Right" 2 "Center" 3 "Left" 
label values lr_obj_cat lr_obj_cat 



*Political trust
corr q10_1 q10_2 q10_3 q10_4 q10_5 q10_6 q10_7
alpha q10_2 q10_5 q10_6 q10_7, item gen(pol_trust) //trust in public administration, political parties, Government, Parliament. 
label var pol_trust "Political trust"



************Dummy variables***************'
recode fairness 1/3=0 4/5=1, gen(fair_dummy)
label def fair_dummy 0 "Unfair" 1 "Fair"
label values fair_dummy fair_dummy 

recode effectiveness 1/3=0 4/5=1, gen(effective_dummy)
label def effective_dummy 0 "Ineffective" 1 "Effective" 
label values effective_dummy effective_dummy 

recode intrusiveness 1/3=0 4/5=1, gen(intrusive_dummy)
label def intrusive_dummy 0 "Reduce personal freedom" 1 "Increase personal freedom" 
label values intrusive_dummy intrusive_dummy 

recode lr_rev 0/5=0 6/10=1, gen(lr_dummy)
label def lr_dummy 0 "Not left" 1 "Left" 
label values lr_dummy lr_dummy 




************CONTROL VARIABLES*****************'' 
*Gender 
qui tab gender //Missing values from South Africa  
qui tab gender_ZA 

replace gender=1 if gender==1 | gender_ZA==2 
replace gender=2 if gender==2 | gender_ZA==1 

recode gender (1=1) (2=0) //male = 0 female = 1 
label def gender 0 Male, add

*Vegetarian
qui tab q15_4 //vegetarian 
recode q15_4 2=0, gen(vegetarian) 
label define vegetarian 0"No" 1"Yes" 
label var vegetarian vegetarian

*Climate concern 
recode q16 1=4 2=3 3=2 4=1, gen(climate_concern) //reverse climate concern
label var climate_concern "How worried are you about climate change? [q16]"
label def climate_concern 1"Not at all worried" 2"Not very worried" 3"Somewhat worried" 4"Very worried"
label val climate_concern climate_concern
clonevar cc=climate_concern
drop climate_concern 

*Habits 
recode q15_6 1=1 2=0, gen(own_car_yn)
recode q15_7 1=1 2=0, gen(drive_car_day)
recode q15_1 1=1 2=0, gen (meat_con_yn)
recode q15_2 1=1 2=0, gen (meat_con_day)

*Education 
qui tab educ //education the US
rename educ education_US 
qui tab education_BR //education Brazil  
qui tab education_DE //education Germany
qui tab education_in //education India 
rename education_in education_IN 
qui tab education_ZA //education South Africa 


gen education=.
label var education Education
label define education 1"Low" 2"Medium" 3"High"
label val education education
replace education=1 if education_BR==1 | education_BR==2 | education_BR==3 | education_BR==4
replace education=2 if education_BR==5 | education_BR==6
replace education=3 if education_BR==7 | education_BR==8 | education_BR==9 | education_BR==10

replace education=1 if education_DE==1 | education_DE==2 | education_DE==3 | education_DE==4
replace education=2 if education_DE==5 | education_DE==6
replace education=3 if education_DE==7 | education_DE==8 | education_DE==9 | education_DE==10

replace education=1 if education_IN==1 | education_IN==2 | education_IN==8
replace education=2 if education_IN==3 | education_IN==4
replace education=3 if education_IN==5 | education_IN==6 | education_IN==7

replace education=1 if education_US==1
replace education=2 if education_US==2 | education_US==3 | education_US==4
replace education=3 if education_US==5 | education_US==6

replace education=1 if education_ZA==1 | education_ZA==2 | education_ZA==3 | education_ZA==4
replace education=2 if education_ZA==5 | education_ZA==6
replace education=3 if education_ZA==7 | education_ZA==8 | education_ZA==9 | education_ZA==10

*Urban/rural 

qui tab urban 
recode urban 777=. //26 observations in Germany 'weiss nicht'

gen urban_all=. 
label var urban_all urban_all
label define urban_all 1"Urban" 2"Suburban" 3"Rural" 
label val urban_all urban_all 
replace urban_all=1 if urban==1 | Urban_ZA==1 
replace urban_all=2 if urban==2 | Urban_ZA==2 
replace urban_all=3 if urban==3 | Urban_ZA==3 | urban==4 |  urban==5 |  urban==6 
 

*Personal income
tab profile_gross_hhold_BR //pinc Brazil 
rename profile_gross_hhold_BR pinc_br 
tab pinc //pinc Germany
rename pinc pinc_de 
tab gross_personal_in //pinc India
rename gross_personal_in pinc_in 
tab profile_gross_personal //pinc US 
rename profile_gross_personal pinc_us 
tab personal_income_ZA //pinc South Africa 
rename personal_income_ZA pinc_za 


label def income 1"Low" 2"Medium" 3"High"
gen pinc=.
label var pinc "Private income"
label val pinc income
replace pinc=1 if pinc_br==1 | pinc_br==2 | pinc_br==3
replace pinc=2 if pinc_br==4 | pinc_br==5 | pinc_br==6 | pinc_br==7 | pinc_br==8 | pinc_br==9
replace pinc=3 if pinc_br==10 | pinc_br==11 | pinc_br==12 | pinc_br==13 | pinc_br==14 | pinc_br==15

replace pinc=1 if pinc_de==1 | pinc_de==2 | pinc_de==3
replace pinc=2 if pinc_de==4 | pinc_de==5 | pinc_de==6 | pinc_de==7 | pinc_de==8
replace pinc=3 if pinc_de==9 | pinc_de==10 | pinc_de==11 | pinc_de==12

replace pinc=1 if pinc_in==1 | pinc_in==2 | pinc_in==3
replace pinc=2 if pinc_in==4 | pinc_in==5 | pinc_in==6 | pinc_in==7
replace pinc=3 if pinc_in==8 | pinc_in==9 | pinc_in==10 | pinc_in==11

replace pinc=1 if pinc_us==1 | pinc_us==2 | pinc_us==3
replace pinc=2 if pinc_us==4 | pinc_us==5 | pinc_us==6 | pinc_us==7 | pinc_us==8 | pinc_us==9
replace pinc=3 if pinc_us==10 | pinc_us==11 | pinc_us==12 | pinc_us==13 | pinc_us==14 | pinc_us==15 | pinc_us==16

replace pinc=1 if pinc_za==1 | pinc_za==2 | pinc_za==3 | pinc_za==4
replace pinc=2 if pinc_za==5 | pinc_za==6 | pinc_za==7 | pinc_za==8 | pinc_za==9 | pinc_za==10 | pinc_za==11 | pinc_za==12 | pinc_za==13| pinc_za==14
replace pinc=3 if pinc_za==15 | pinc_za==16 | pinc_za==17 | pinc_za==18 | pinc_za==19


**** Categorical variables --> dummy variables
qui tab age_3,			gen(agecat)
qui tab education,		gen(educat)
qui tab pinc,			gen(inccat)
qui tab fairness,		gen(faircat)
qui tab effectiveness,	gen(effectivecat)
qui tab intrusiveness,	gen(intrusivecat) 




*******************************Analysis*********************************

**Percent on IVs**

dtable i.fairness i.effectiveness i.intrusive_rev i.lr_rev_3, by(country) sample(, statistics(perc)) export(dtable_IVs.docx, as(docx) replace) 

eststo clear

eststo: mean fuel_rationing, over(country)

eststo: mean food_rationing, over(country)

esttab using "mean.rtf", nogaps noeqlines compress b(3) wide se replace 



***Main regression table******** 

eststo clear 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==5, robust //DE 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==6, robust //BR 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==5, robust //DE 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==6, robust //BR 

esttab using "rationing_all.rtf", label eform nogaps noeqlines compress b(2) one se stats(N aic bic, fmt(3 3 0) labels("Observations" "AIC" "BIC")) varwidth(15) modelwidth(2) nobase mtitles("US" "South Africa" "India" "Germany" "Brazil" "US" "South Africa" "India" "Germany" "Brazil") replace




******With OLS********** //For supplementary
eststo clear 
**Fuel 
eststo: reg fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: reg fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA

eststo: reg fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: reg fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //DE 

eststo: reg fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //BR 

**Meat
eststo: reg food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: reg food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA

eststo: reg food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: reg food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==5, robust //DE 

eststo: reg food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==6, robust //BR 

esttab using "rationing_all_ols.rtf", label nogaps noeqlines compress b(2) one se stats(N r2 aic bic, labels("Observations" "R2" "AIC" "BIC")) varwidth(15) modelwidth(2) nobase mtitles("US" "South Africa" "India" "Germany" "Brazil" "US" "South Africa" "India" "Germany" "Brazil") replace


*********Combomarginsplot all countries********* 

**Fairness** 

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_all, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_all, replace)

combomarginsplot fair_fuel_all fair_food_all, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) region(lc(black)) size(medsmall) pos(6) col(2) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(1 `""Very" "unfair""' 2 3 4 5 `""Very" "Fair""', nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(dot)) ///
	title("") ///
	xtitle("{bf:Perceived fairness}") ///
	ytitle("Pr(Accept)") /// titles y-axis
	subtitle("Fairness", box bexpand) /// makes subtitle
	name(fairness_all, replace)


**Intrusiveness** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) saving(intrusive_fuel_all, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) saving(intrusive_food_all, replace)


combomarginsplot intrusive_fuel_all intrusive_food_all, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) region(lc(black)) size(medsmall) pos(6) col(2) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(1 `""Increases my" " freedom a lot""' 2 3 4 5 `""Restricts my" " freedom a lot""' , nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1 .6, lp(dot)) ///
	title("") ///
	xtitle("{bf:Perceived intrusiveness}") ///
	ytitle("Pr(Accept)") /// titles y-axis
	subtitle("Intrusiveness", box bexpand) /// makes subtitle
	name(intrusiveness_all, replace)
	
**Effectiveness** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(effective_fuel_all, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(effective_food_all, replace)

combomarginsplot effective_fuel_all effective_food_all, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) region(lc(black)) size(medsmall) pos(6) col(2) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(1 `""Very" "ineffective""' 2 3 4 5 `""Very" "effective""', nogrid) /// specifies x-axis range and changes gridlines
	title("") ///
	ylab(.1(.1).6) ///
	yline(.1 .6, lp(dot)) ///
	xtitle("{bf:Perceived effectiveness}") ///
	ytitle("Pr(Accept)") /// titles y-axis
	subtitle("Effectiveness", box bexpand) /// makes subtitle
	name(effectiveness_all, replace)
	
**Ideology** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_all, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_all, replace)

combomarginsplot lr_fuel_all lr_food_all, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) region(lc(black)) size(medsmall) pos(6) col(2) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(0 `""To the" "far right""' 1 2 3 4 5 6 7 8 9 10 `""To the" "far left""' , nogrid) /// specifies x-axis range and changes gridlines
	title("") ///
	ylab(.1(.1).6) ///
	yline(.1, lp(dot)) ///
	xtitle("{bf:Political ideology (right-left)}") ///
	ytitle("Pr(Accept)") /// titles y-axis
	subtitle("Political ideology", box bexpand) /// makes subtitle
	name(lr_all, replace)

**Combine figures** 
grc1leg2 fairness_all intrusiveness_all effectiveness_all lr_all, ycommon xsize(7) ysize(7) scale(.7) imargin(0 10 4 0) name(pooled_results, replace) 

gr export "Figures/pooled_results.emf", as(emf) replace ///
	name("pooled_results", replace)
	
	
	
****Tables for above figure****** 

//Fairness
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post
estimates store m1 

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m2 

esttab m1 m2 using "pooled_fairness.rtf", label nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) ti(Predictive margins fairness) mtitles("Fuel rationing" "Meat rationing") replace

//Intrusiveness

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(intrusiveness=(1(1)5)) predict(outcome(3)) post
estimates store m3

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(intrusiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m4

esttab m3 m4 using "pooled_intrusiveness.rtf", label nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) mtitles("Fuel rationing" "Meat rationing") replace


//Effectiveness

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post
estimates store m5

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m6

esttab m5 m6 using "pooled_effectiveness.rtf", label nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) mtitles("Fuel rationing" "Meat rationing") replace

//Ideology 

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store m7

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 i.country [pweight=weight], robust 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post 
estimates store m8

esttab m7 m8 using "pooled_lr.rtf", label nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) mtitles("Fuel rationing" "Meat rationing") replace

	

********Combomarginsplot fairness full********* 
****US*****
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_us, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_us, replace)

combomarginsplot fair_fuel_us fair_food_us, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	yline(.6, lp(dot)) ///
	xtitle("Fairness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("US", box bexpand) /// makes subtitle
	name(fair1, replace)
	

 
******South Africa******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_za, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_za, replace)

combomarginsplot fair_fuel_za fair_food_za, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	yline(.8, lp(.)) ///
	xtitle("Fairness") ///
	ytitle("") /// titles y-axis
	subtitle("South Africa", box bexpand) /// makes subtitle
	name(fair2, replace)

	
******India******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_in, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_in, replace)

combomarginsplot fair_fuel_in fair_food_in, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	yline(.1, lp(.)) ///
	xtitle("Fairness") ///
	ytitle("") /// titles y-axis
	subtitle("India", box bexpand) /// makes subtitle
	name(fair3, replace)

	
******Germany******** 
ologit fuel_ration_infavor fairness effectiveness intrusivenes  lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_de, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_de, replace)

combomarginsplot fair_fuel_de fair_food_de, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	yline(.6, lp(.))
	xtitle("Fairness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("Germany", box bexpand) /// makes subtitle
	name(fair4, replace)

	
******Brazil******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_fuel_br, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(fairness=(1(1)5)) predict(outcome(3)) saving(fair_food_br, replace)

combomarginsplot fair_fuel_br fair_food_br, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	yline(.6, lp(.)) ///
	xtitle("Fairness") ///
	ytitle("") /// titles y-axis 
	subtitle("Brazil", box bexpand) /// makes subtitle
	name(fair5, replace)
	

grc1leg fair1 fair2 fair3 fair4 fair5, ycommon name(fairness, replace)

gr export "Figures/fairness.emf", as(emf) replace ///
	name("fairness", replace)

*******Table for the above figure**********


ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m1 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m2 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m3

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m4

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m5

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m6 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m7

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m8 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m9

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br

margins, at(fairness=(1(1)5)) predict(outcome(3)) post 
estimates store m10 

esttab m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 using "fairness_main.rtf", nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) ti(Predictive margins Fairness) mtitles("US fuel" "US meat" "South Africa fuel" "South Africa meat" "India fuel" "India meat" "Germany fuel" "Germany meat" "Brazil fuel" "Brazil meat") replace

 
 

 
********Combomarginsplot intrusiveness********* 
 
****US*****
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_fuel_us, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_food_us, replace)

combomarginsplot int_fuel_us int_food_us, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.6, lp(.)) ///
	title("") ///
	xtitle("Intrusiveness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("US", box bexpand) /// makes subtitle
	name(int1, replace) 
	

 
******South Africa******** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_fuel_za, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_food_za, replace)

combomarginsplot int_fuel_za int_food_za, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	title("") ///
	ylab(.1(.1).6) ///
	yline(.1 .6, lp(.)) ///
	xtitle("Intrusiveness") ///
	ytitle("") /// titles y-axis
	subtitle("South Africa", box bexpand) /// makes subtitle
	name(int2, replace) 

	
******India******** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_fuel_in, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_food_in, replace)

combomarginsplot int_fuel_in int_food_in, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Intrusiveness") ///
	ytitle("") /// titles y-axis
	subtitle("India", box bexpand) /// makes subtitle
	name(int3, replace) 

	
******Germany******** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_fuel_de, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_food_de, replace)

combomarginsplot int_fuel_de int_food_de, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	title("") ///
	xtitle("Intrusiveness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("Germany", box bexpand) /// makes subtitle
	name(int4, replace) 

	
******Brazil******** 
ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_fuel_br, replace)

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br

margins, at(intrusive_rev=(1 2 3 4 5)) predict(outcome(3)) saving(int_food_br, replace)

combomarginsplot int_fuel_br int_food_br, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Intrusiveness") ///
	ytitle("") /// titles y-axis 
	subtitle("Brazil", box bexpand) /// makes subtitle
	name(int5, replace) 
	

grc1leg int1 int2 int3 int4 int5, name(intrusiveness, replace) 

gr export "Figures/intrusiveness.emf", as(emf) replace ///
	name("intrusiveness", replace)


 
 
*******Table for the above figure**********


ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n1 

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n2 

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n3

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n4

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n5 

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n6 

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n7

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n8 

ologit fuel_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n9

ologit food_ration_infavor fairness effectiveness intrusive_rev lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br

margins, at(intrusive_rev=(1(1)5)) predict(outcome(3)) post 
estimates store n10 

esttab n1 n2 n3 n4 n5 n6 n7 n8 n9 n10 using "intrusiveness_main.rtf", nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) ti(Predictive margins Intrusiveness) mtitles("US fuel" "US meat" "South Africa fuel" "South Africa meat" "India fuel" "India meat" "Germany fuel" "Germany meat" "Brazil fuel" "Brazil meat") replace

 
 

 
********Combomarginsplot left-right ********* 
 
****US*****
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_us, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_us, replace)

combomarginsplot lr_fuel_us lr_food_us, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.6, lp(.)) ///
	title("") ///
	xtitle("Ideology (right-left)") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("US", box bexpand) /// makes subtitle
	name(lr1, replace) 
	

 
******South Africa******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_za, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_za, replace)

combomarginsplot lr_fuel_za lr_food_za, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Ideology (right-left)") ///
	ytitle("") /// titles y-axis
	subtitle("South Africa", box bexpand) /// makes subtitle
	name(lr2, replace) 

	
******India******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_in, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_in, replace)

combomarginsplot lr_fuel_in lr_food_in, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Ideology (right-left)") ///
	ytitle("") /// titles y-axis
	subtitle("India", box bexpand) /// makes subtitle
	name(lr3, replace) 

	
******Germany******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_de, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_de, replace)

combomarginsplot lr_fuel_de lr_food_de, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.6, lp(.)) ///
	title("") ///
	xtitle("Ideology (right-left)") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("Germany", box bexpand) /// makes subtitle
	name(lr4, replace) 

	
******Brazil******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_fuel_br, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) saving(lr_food_br, replace)

combomarginsplot lr_fuel_br lr_food_br, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Ideology (right-left)") ///
	ytitle("") /// titles y-axis 
	subtitle("Brazil", box bexpand) /// makes subtitle
	name(lr5, replace) 
	

grc1leg lr1 lr2 lr3 lr4 lr5, cols(3) name(lr, replace) 

gr export "Figures/lr.emf", as(emf) replace ///
	name("lr", replace)


 
 

***Table for the above figure**********


ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l1 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post 
estimates store l2 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l3 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post 
estimates store l4 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l5 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l6 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l7 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post 
estimates store l8 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br  

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post
estimates store l9

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(lr_rev=(0(1)10)) predict(outcome(3)) post 
estimates store l10 



esttab l1 l2 l3 l4 l5 l6 l7 l8 l9 l10 using "lr_main.rtf", nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) ti(Predictive margins Ideology) mtitles("US fuel" "US meat" "South Africa fuel" "South Africa meat" "India fuel" "India meat" "Germany fuel" "Germany meat" "Brazil fuel" "Brazil meat") replace
 

 
 
 
 
 
****************Combomarginsplot effectiveness*********************
 
 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_fuel_us, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_food_us, replace)

combomarginsplot eff_fuel_us eff_food_us, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) region(lp(solid)) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.6, lp(.)) ///
	title("") ///
	xtitle("Effectiveness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("US", box bexpand) /// makes subtitle
	name(eff1, replace) 
	

 
******South Africa******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_fuel_za, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_food_za, replace)

combomarginsplot eff_fuel_za eff_food_za, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) /// 
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Effectiveness") ///
	ytitle("") /// titles y-axis
	subtitle("South Africa", box bexpand) /// makes subtitle
	name(eff2, replace) 

	
******India******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_fuel_in, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_food_in, replace)

combomarginsplot eff_fuel_in eff_food_in, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Effectiveness") ///
	ytitle("") /// titles y-axis
	subtitle("India", box bexpand) /// makes subtitle
	name(eff3, replace) 

	
******Germany******** 
ologit fuel_ration_infavor fairness effectiveness intrusivenes  lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_fuel_de, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_food_de, replace)

combomarginsplot eff_fuel_de eff_food_de, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1 .6, lp(.)) ///
	title("") ///
	xtitle("Effectiveness") ///
	ytitle("Predicted acceptability of rationing") /// titles y-axis
	subtitle("Germany", box bexpand) /// makes subtitle
	name(eff4, replace) 

	
******Brazil******** 
ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_fuel_br, replace)

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) saving(eff_food_br, replace)

combomarginsplot eff_fuel_br eff_food_br, ///
	labels("Fossil fuel rationing" "Meat rationing") ///
	plotopts(lwidth(medthick) lcolor(%70) msize(small) mcolor(%75)) ///
	legend(ring(1) size(small) pos(3) col(1) margin(small)) /// legend options
	graphregion(margin(medsmall)) ///
	plotregion(margin(medlarge)) /// 
	recastci(rarea) ciopts(fcolor(%40)) /// 
	scheme(white_tableau) /// changes scheme 
	xlab(, nogrid) /// specifies x-axis range and changes gridlines
	ylab(.1(.1).6) ///
	yline(.1, lp(.)) ///
	title("") ///
	xtitle("Effectiveness") ///
	ytitle("") /// titles y-axis 
	subtitle("Brazil", box bexpand) /// makes subtitle
	name(eff5, replace) 
	

grc1leg eff1 eff2 eff3 eff4 eff5, name(effectiveness, replace)

gr export "Figures/effectiveness.emf", as(emf) replace ///
	name("effectiveness", replace)

 

*******Table for the above figure**********


ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m1 

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 1 [pweight=weight], robust //US

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m2 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m3

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 3 [pweight=weight], robust //za 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m4

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m5

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 4 [pweight=weight], robust //in

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m6 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m7

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 5 [pweight=weight], robust //de 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m8 

ologit fuel_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br 

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m9

ologit food_ration_infavor fairness effectiveness intrusiveness lr_rev i.gender i.pinc i.urban_all i.education i.age_3 if country == 6 [pweight=weight], robust //br

margins, at(effectiveness=(1(1)5)) predict(outcome(3)) post 
estimates store m10 

esttab m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 using "effectiveness_main.rtf", nogaps noeqlines compress b(2) ci varwidth(15) modelwidth(2) ti(Predictive margins Fairness) mtitles("US fuel" "US meat" "South Africa fuel" "South Africa meat" "India fuel" "India meat" "Germany fuel" "Germany meat" "Brazil fuel" "Brazil meat") replace

 
 
 **********************************************************************************
*************************************Supplementary********************'''************* 
****************************************************************************************





*Sample descriptives* 
dtable i.gender i.age_3 i.education i.pinc i.urban_all, by(country) column(by(hide)) export(dtable_descriptives.docx, as(docx) replace) 



**Mean variables** 

eststo clear 
estpost tabstat fuel_rationing food_rationing, by(country) statistics(count mean sd) col(stat)
esttab using "DVs.rtf", cells("count mean sd") one replace



eststo clear 
estpost tabstat gender pinc urban_all education age_3, by(country) statistics(count mean sd) col(stat)
esttab using "DVs.rtf", cells("count mean sd") one replace


**Descriptive statisics** //Table S1 

eststo clear 
estpost tabstat fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev, by(country) /// 
statistics(N mean sd) columns(statistics)
esttab using "descriptive.rtf", cells("count mean sd") replace


**Spearman's rank correlation**

***US***** 
Spearman fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev if country == 1, stats(rho) st(.001)  
matrix US = r(Rho) 
esttab matrix(US, fmt(%5.2f)) using corrtable_us.rtf, noobs replace

*VIF* 
qui reg fuel_rationing fairness effectiveness intrusiveness if country == 1
estat vif //is VIF is morethan 5 for any variable, we might have multicollinearity problem 
 

**Factor analysis** 
factor fairness effectiveness intrusiveness if country == 1 


*South Africa* 
Spearman fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev if country == 3, stats(rho) st(.001)  
matrix ZA = r(Rho) 
esttab matrix(ZA, fmt(%5.2f)) using corrtable_za.rtf, noobs replace

qui reg fuel_rationing fairness effectiveness intrusiveness if country == 3
estat vif //is VIF is morethan 5 for any variable, we might have multicollinearity problem 

**Factor analysis** 
factor fairness effectiveness intrusiveness if country == 3

*India* 
Spearman fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev if country == 4, stats(rho) st(.001)  
matrix IN = r(Rho) 
esttab matrix(IN, fmt(%5.2f)) using corrtable_in.rtf, noobs replace

qui reg fuel_rationing fairness effectiveness intrusiveness if country == 4
estat vif //is VIF is morethan 5 for any variable, we might have multicollinearity problem 

**Factor analysis** 
factor fairness effectiveness intrusiveness if country == 4

*Germany* 
Spearman fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev if country == 5, stats(rho) st(.001)  
matrix DE = r(Rho) 
esttab matrix(DE, fmt(%5.2f)) using corrtable_de.rtf, noobs replace

qui reg fuel_rationing fairness effectiveness intrusiveness if country == 5
estat vif //is VIF is morethan 5 for any variable, we might have multicollinearity problem 

**Factor analysis** 
factor fairness effectiveness intrusiveness if country == 5

*Brazil* 
Spearman fuel_rationing food_rationing fairness effectiveness intrusiveness lr_rev if country == 6, stats(rho) st(.001)  
matrix BR = r(Rho) 
esttab matrix(BR, fmt(%5.2f)) using corrtable_br.rtf, noobs replace

qui reg fuel_rationing fairness effectiveness intrusiveness if country == 6
estat vif //is VIF is morethan 5 for any variable, we might have multicollinearity problem 

**Factor analysis** 
factor fairness effectiveness intrusiveness if country == 6



**Robustness checks** 

* Subset of respondents who completed the survey within +/- one standard deviations' time
preserve
sum tot_time, d
drop if tot_time < (r(mean) - 1 * r(sd) ) | tot_time > (r(mean) + 1 * r(sd)) //72 obs dropped

eststo clear 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==5, robust //DE 

eststo: ologit fuel_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==6, robust //BR 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==1, robust //US 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==3, robust //ZA 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==4, robust //IN 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==5, robust //DE 

eststo: ologit food_rationing fairness effectiveness intrusive_rev lr_rev i.gender i.age_3 i.education i.urban_all i.pinc [pweight=weight] if country==6, robust //BR 

esttab using "onestddev_all.rtf", label eform nogaps noeqlines compress b(2) one se stats(N aic bic, labels("Observations" "AIC" "BIC")) varwidth(15) modelwidth(2) nobase mtitles("US" "South Africa" "India" "Germany" "Brazil" "US" "South Africa" "India" "Germany" "Brazil") replace


restore 






